Methods for Detecting, Diagnosing and Treating Human Renal Cell Carcinoma

ABSTRACT

Gene expression profiling and hierarchical clustering analysis readily identify differential gene expressions in normal renal epithelial cells and renal cell carcinomas. Genes identified by this analysis would be useful for diagnosis, prognosis and development of targeted therapy for the prevention and treatment of conventional renal cell carcinoma.

CROSS-REFERENCE TO RELATED APPLICATION

This is a continuation application under 35 U.S.C. §120 of pending nonprovisional application U.S. Ser. No. 10/938,973, filed Sep. 10, 2004, which claims benefit of provisional application U.S. Ser. No. 60/539,838, filed Jan. 28, 2004, now abandoned, and of provisional application U.S. Ser. No. 60/502,038, filed Sep. 10, 2003, now abandoned, the entirety of all of which are hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to the field of cancer research. More specifically, the present invention relates to gene expression profiling for human renal cell carcinoma.

2. Description of the Related Art

Renal cell carcinoma (RCC) represents a major health issue. The American Cancer Society predicts 31,900 new cases will be diagnosed in the United States alone in the year 2003, with 11,900 people dying of the disease. When clinically localized or even locally advanced, renal cell carcinoma can be surgically resected for cure using a variety of approaches. With metastatic progression, however, renal cell carcinoma is incurable, and existing systemic therapies are largely ineffective in impacting disease response or patient survival. The lack of effective systemic therapy for metastatic renal cell carcinoma is, in part, due to a fundamental lack of understanding of the molecular events that result in cellular transformation, carcinogenesis, and progression in human kidney.

The advent of gene array technology has allowed classification of disease states at molecular level by examining changes in all mRNAs expressed in cells or tissues. Gene expression fingerprints representing large numbers of genes may allow precise and accurate grouping of renal cell carcinoma. Moreover, large scale gene expression analysis have the potential of identifying a number of differentially expressed genes in renal cell carcinoma compare to normal renal epithelial cells. These genes or markers may further be tested for clinical utility in the diagnosis and treatment of renal cell carcinoma.

Thus, the identification of novel renal cell carcinoma markers to be used for detection, diagnosis and development of effective therapy against the disease remains a high priority. The prior art is deficient in understanding the molecular differences between renal cell carcinoma and normal renal epithelium. The present invention fulfills this need in the art by providing gene expression profiling for these two types of tissues.

SUMMARY OF THE INVENTION

The present invention identifies genes with a differential pattern of expression between different subtypes of renal cell carcinomas (RCC) and normal renal epithelium. These genes and their products can be used to develop novel diagnostic and therapeutic markers for the treatment of renal cell carcinomas.

Genomic profiling of conventional renal cell carcinoma tissues and patient-matched normal kidney tissue samples was carried out using stringent statistical analyses (ANOVA with full Bonferroni corrections). Subtypes of renal cell carcinoma include stage I, II, III, and IV (reflecting differences in tumor size, lymph node and organ metastasis), stage I papillary renal cell carcinoma, and benign oncocytoma. Hierarchical clustering of the expression data readily distinguished normal tissue from renal cell carcinomas. The identified genes were verified by real-time FCR and immunohistochemical analyses.

Different subtypes of conventional renal cell carcinomas can be diagnosed either by drawing blood and identifying secreted gene products specific to renal cell carcinoma or by doing a biopsy of the tissue and then identify specific genes that are altered when renal cell carcinoma is present. An example of when this may be especially important is in distinguishing the deadly conventional renal cell carcinomas (account for 85% of all renal cell carcinomas) from renal oncocytoma (benign renal cell carcinoma) as well as identifying the histologic subtypes of papillary and sarcomatoid renal cell carcinoma. Identification of specific genes will also help in determining which patients will have a good prognosis verses that of a poor prognosis. In addition, subsets of genes identified in the present invention can be developed as targets for therapies that could cure, prevent, or stabilize the disease. Thus, results from the present invention could be used for diagnosis, prognosis, and development of therapies to treat or prevent renal cell carcinoma.

In one embodiment, there are provided methods of detecting conventional or clear cell renal cell carcinoma based on over-expression and/or down-regulation of a number of genes disclosed herein. In another embodiment, conventional or clear cell renal cell carcinoma is detected based on decreased expression of type III TGF-β receptor.

In yet another embodiment, there are provided methods of detecting stage I conventional or clear cell renal cell carcinoma based on over-expression and/or down-regulation of a number of genes disclosed herein.

The present invention also provides methods of detecting stage II conventional or clear cell renal cell carcinoma based on over-expression and/or down-regulation of a number of genes disclosed herein.

The present invention also provides methods of detecting papillary renal cell carcinoma or benign oncocytoma based on over-expression and/or down-regulation of a number of genes disclosed herein.

In another embodiment, there is provided a method of targeting conventional or clear cell renal cell carcinoma cells based on generating antibodies or small molecules directed against a cell surface molecule over-expressed in conventional renal cell carcinoma cells.

In yet another embodiment, there is provided a method of treating conventional or clear cell renal cell carcinoma by replacing down-regulated tumor suppressor gene in conventional renal cell carcinoma.

Other and further aspects, features, and advantages of the present invention will be apparent from the following description of the presently preferred embodiments of the invention. These embodiments are given for the purpose of disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows hierarchical clustering of genes expressed in normal renal cortex (12 patient tissue samples) verse stage I conventional renal cell carcinoma (6 patient tissue samples). Red indicates that a gene is highly expressed and green is indicative of low expression. Four hundred eighty eight genes were depicted in FIG. 1A. FIG. 1B shows hierarchical clustering of genes expressed in normal renal cortex (12 patient tissue samples) verse stage II conventional renal cell carcinoma (6 patient tissue samples). Red indicates that a gene is highly expressed and green is indicative of low expression. Six hundred twenty eight genes were depicted in FIG. 1B. FIG. 1C shows hierarchical clustering of genes selected from a Venn analysis in which the chosen genes were expressed in common in both stage I and II at a 99% confidence level. One hundred eighty eight genes were depicted in FIG. 1C. C, cancer cells; N, normal cells; S1, stage 1; S2, stage 2.

FIG. 2 shows TGF-β1 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR TGF-β1 mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 3 shows TGF-α mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. TGF-α mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 4 shows adrenomedulin mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. Adrenomedulin mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 5 shows TGF-tβ2 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. TGF-β32 mRNA levels were not altered between normal and tumor matched samples.

FIG. 6 shows TGF-133 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. TGF-β3 mRNA levels were not altered between normal and tumor matched samples.

FIG. 7 shows tumor suppressor gene Wilms Tumor 1 (WT1) mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. WT1 mRNA levels were down-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts.

FIG. 8 shows von Hippel Lindau mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. A small percentage of tumor tissues demonstrated attenuated von Hippel Lindau mRNA levels when compared to matched normal tissue

FIG. 9 shows calbindin mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. Calbindin mRNA was completely lost in all stage I renal cell carcinoma. p<0.05 compared to matched control. *Stage I tumor: 0±0; stage III tumor: 0.0009±0.0004; stage IV tumor: 0.003±0.0004/

FIG. 10 shows MUC1 mRNA expression in stages I-IV renal cell carcinoma as measured by real time PCR. MUC1 mRNA levels were down-regulated in all tumor tissues as early as stage I. *p<0.05 compared to matched control.

FIGS. 11A-11B show stepwise loss of type III α receptor (TBR3) and type II TGF-β receptor (TBR2) mRNA expression during renal cell carcinogenesis and progression in patient tissue samples. FIG. 11A shows gene array data from 10 patients—five diagnosed with localized renal cell carcinoma and five with metastatic disease. ‘+’ (P<0.05) indicates statistical difference for TBR3 mRNA levels as compared to normal tissue and ‘*’ (P<0.28) indicates statistical difference for TBR2 mRNA levels as compared to normal controls. Data are expressed as mean±s.e. FIG. 11B shows real-time RT-PCR verification of TBR1, TBR2, and TBR3 mRNA levels of tissue samples described in FIG. 11A. Data are expressed as mean±s.d.

FIG. 12 shows immunohistochemistry of patient tissue demonstrating loss of type III α receptor (TBR3) expression (top row) in all tumors, loss of type II α receptor (TBR2) expression (middle row) in patients diagnosed with metastatic tumors, and no change in type I α receptor (TBR1) protein expression (bottom row).

FIG. 13 demonstrates down-regulation of TGF-3-regulated genes in human tumor tissues by real-time PCR. Genes known to be up-regulated by α are suppressed in tumor tissues. Down-regulation of collagen IV type 6, fibulin 5, and connective tissue growth factor (CTGF) mRNA in tumor tissues were compared to matched normal tissue controls. Values were normalized to 18 s mRNA. Each matching tumor value was compared to its respective normal control. The mean±s.d. was calculated for each sample group with n values of 10-15 matched samples.

FIGS. 14A-14B show tumor cell lines that lose type III α receptor (TBR3) and type I TGF-β receptor (TBR2) expression. FIG. 14A shows semi-quantitative RT-PCR measurements of mRNA levels of TBR1, TBR2, and TBR3 for UMRC3, UMRC6 and normal renal epithelial (NRE) cells. FIG. 14B shows immunohistochemistry of protein expression for TBR1, TBR2, and TBR3 (×40 magnification).

FIGS. 15A-15B show loss of type III TGF-β receptor (TBR3) and type II α receptor (TBR2) expression in renal tumor cell lines correlate with loss of TGF-3-regulated growth inhibitory and transcriptional responses. FIG. 15A shows cell proliferation was inhibited as assessed by DNA content 3 days after α treatment. Percent of each respective untreated control was used for comparisons. Transient transfection using 3TP/lx along with a renilla luciferase control demonstrates loss of responsiveness to 2 ng/ml TGF-β1 with loss of TGF-β receptor expression (FIG. 15B). Firefly luciferase activity was normalized using the ratio of firefly luciferase/renilla luciferase. Data are expressed as mean±s.d.

FIG. 16A demonstrates RT-PCR derived mRNA expression of type III α receptor (TBR3), type II α receptor (TBR2), and type I α receptor (TBR1) in UMRC3 cells and cells stably transfected with TBR2 and TBR3. FIG. 16B shows UMRC3 cells stably transfected with type II TGF-β receptor (UMRC3+TBR2) or type II and type III TGF-β receptor (UMRC3+TBR2+TBR3) demonstrated attenuated cell proliferation following the administration of exogenous TGF-β1 as compared to that of UMRC3 cells. FIG. 16C shows UMRC3 cells, UMRC3+TBR2 cells, and UMRC3+TBR2+TBR3 stable cell lines transfected with 3TP/lux were treated with or without TGF-β and examined for luciferase activity. FIG. 16D shows real-time PCR measuring mRNA levels for collagen IV type 6 in UMRC3, UMRC3+TBR2 cells, and UMRC3+TBR2+TBR3 cells in the presence of 2 ng/ml TGF-β1 for 24 h. FIG. 16E shows colony formation assay demonstrates that UMRC3+TBR2+TBR3 cells have completely lost anchorage-independent growth, while attenuated growth in UMRC3+TBR2 cells occurs as compared to that of UMRC3 cells. The number of colonies were stained and counted after 45 days of growth. Data are expressed as mean±s.d.

FIG. 17A shows growth inhibition after re-expressing human type III TGF-β3 receptor (TBR3) in UMRC3 cells. UMRC3 cells were stably transfected with TBR3 or infected using an adenoviral vector expressing TBR3. Cells were plated in culture dishes at 20,000 cells/well. Cell number was determined at the indicated times using a Coulter cell counter. FIG. 17B shows RT-PCR data demonstrating the mRNA expression levels of type I, II, or III TGF-β receptors (TBR1, TBR2, TBR3) in UMRC3 cells in the presence or absence of the adenoviral vector expressing TBR3. Unmodified UMRC3 cells only express TBR1.

FIG. 18 shows re-expression of human type II or III TGF-β receptors (TBR2 or TBR3) inhibits tumor growth in nude mice. One million UMRC3 cells stably transfected with human type II or type III TGF-β receptors were implanted into nude mice ectopically and tumor growth was measured weekly. Tumor volume (mm³) was calculated by width×length×height×0.5236.

FIG. 19 shows hierarchical clustering of genes expressed in normal renal cortex verse stage I papillary renal cell carcinoma. Red indicates that a gene is highly expressed and green is indicative of low expression.

FIG. 20 shows hierarchical clustering of genes expressed in normal renal cortex verse benign oncocytoma. Red indicates that a gene is highly expressed and green is indicative of low expression.

FIG. 21 shows venn analysis of gene distribution among stage I renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma.

FIG. 22 shows venn analysis of gene distribution among stage II renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma.

DETAILED DESCRIPTION OF THE INVENTION

High-throughput technologies for assaying gene expression, such as high-density oligonucleotide and cDNA microarrays, offer the potential to identify clinically relevant genes differentially expressed between normal and tumor cells. The present invention discloses a genome-wide examination of differential gene expression between renal cell carcinomas (RCC) and normal renal epithelial cells.

Currently, there are no proven molecular markers useful clinically for the diagnosis, staging, or prognosis of sporadic renal cell carcinoma. The present invention detects genes that have differential expression between renal cell carcinomas and normal renal epithelial cells. The known function of some of these genes may provide insight into the biology of renal cell carcinomas while others may prove to be useful as diagnostic or therapeutic markers against renal cell carcinomas. Subtypes of renal cell carcinomas disclosed herein include stage I, II, III, and IV renal cell carcinomas (reflecting differences in tumor size, lymph node and organ metastasis), stage I papillary renal cell carcinoma, and benign oncocytoma.

The present invention provides methods of detecting conventional renal cell carcinoma based on determining the expression level of a number of genes that are found to have 2-fold or higher differential expression levels between tumor and normal tissue. In general, biological samples (e.g. tissue samples, serum samples, urine samples, saliva samples, blood samples or biopsy samples) are obtained from the individual to be tested and gene expression at RNA or protein level is compared to that in normal tissue. The normal tissue samples can be obtained from the same individual who is to be tested for renal cell carcinoma.

It will be obvious to one of ordinary skill in the art that gene expression can be determined by DNA microarray and hierarchical cluster analysis, real-time PCR, RT-PCR, or northern analysis, whereas secreted gene products can be measured in blood samples by standard procedures.

In one embodiment, there is provided a method of detecting conventional or clear cell renal cell carcinoma based on differential expression of one or more of the following genes or proteins: TGF-β1, TGF-α, adrenomedulin, fibroblast growth factor 2 (FGF2), vascular epidermal growth factor (VEGF), osteonectin, follistatin like-3, inhibin beta A, spondin 2, chemokine X cytokine receptor 4 (CXCR4), fibronectin, neuropilin 1, frizzled homolog 1, insulin-like growth factor binding protein 3, laminin alpha 3, integrin beta 2, semaphorins 6A, semaphorins 5B, semaphorins 3B, caspase 1, sprouty 1, CDH16, PCDH9, compliment component 1-beta, compliment component 1-alpha, compliment component 1-gamma, CD53, CDW52, CD163, CD14, CD3Z, CD24, RAP1, angiopoietin 2, cytokine knot secreted protein, MAPKKKK4, 4-hydroxyphenylpyruvate dioxygenase, pyruvate carboxyknase 2, 11-beta-hydroxysteroid dehydrogenase 2, GAS1, CDKN1, nucleolar protein 3, interferon induced protein 44, NR3C1, vitamin D receptor, hypothetical protein FLJ14957 (Affy #225817_at), metallothionein 2A, metallothionein-If gene, metallothionein 1H, secreted frizzled related protein 1, connective tissue growth factor, and epidermal growth factor.

In another embodiment, there is provided a method of detecting conventional renal cell carcinoma by examining the expression level of type III TGF-β receptor, wherein decreased expression of type III TGF-b receptor indicates the presence of renal cell carcinoma. In general, the expression level of type III TGF-β receptor can be determined at the mRNA or protein level.

The present invention also provides methods of detecting stage I conventional renal cell carcinoma, stage II conventional renal cell carcinoma, stage I papillary renal cell carcinoma, or benign oncocytoma based on over-expression or down-regulation of a number of genes identified in the present invention. The present invention discloses a number of genes that are up- or down-regulated specifically in these subtypes of renal cell carcinoma. Determining the expression levels of these genes would provide specific diagnosis for these different subtypes of renal cell carcinoma.

For example, stage I conventional renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 1, (ii) down-regulation of one or more genes listed in Table 2, or (iii) over-expression of one or more genes listed in Table 1 and down-regulation of one or more genes listed in Table 2. Similarly, stage II conventional renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 3, (ii) down-regulation of one or more genes listed in Table 4, or (iii) over-expression of one or more genes listed in Table 3 and down-regulation of one or more genes listed in Table 4.

The present invention also discloses a number of genes that are up- or down-regulated in both stage I and stage II conventional renal cell carcinoma (Tables 5 and 6 respectively). These genes would also provide diagnosis for stage I or stage II conventional renal cell carcinoma. Hence, stage I or stage II conventional renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 5, or (ii) down-regulation of one or more genes listed in Table 6.

In another embodiment, stage I papillary renal cell carcinoma can be detected based on (i) over-expression of one or more genes listed in Table 8, (ii) down-regulation of one or more genes listed in Table 9, or (iii) over-expression of one or more genes listed in Table 8 and down-regulation of one or more genes listed in Table 9.

In yet another embodiment, benign oncocytoma can be detected based on (i) over-expression of one or more genes listed in Table 10, (ii) down-regulation of one or more genes listed in Table 11, or (iii) over-expression of one or more genes listed in Table 10 and down-regulation of one or more genes listed in Table 11.

In still yet another embodiment, there are provided methods of utilizing genes over-expressed on the cell surface of renal carcinoma tissue to develop antibodies or other small molecules for the purpose of specifically targeting the renal tumor cells. The present invention discloses a number of genes that are up-regulated in stage I renal cell carcinoma (RCC), stage II RCC tumor, stage I papillary RCC, and benign oncocytoma. Antibodies or small molecules directed against proteins encoded by these genes can be linked with a therapeutic drug to deliver drug to the tumor tissue, or be linked with dye, nanoparticle or other imaging agents for cancer imaging. Some of the novel genes identified herein for the first time include, but are not limited to, the following genes: calcitonin receptor-like (206331_at; 210815_s_at); receptor (calcitonin) activity modifying protein 2 (RAMP2; 205779_at); endothelin receptor type B (206701_x_at); beta 2 integrin (202803_s_at); alpha 5 integrin (201389_at); chemokine X cytokine receptor 4 (CXCR4); fibronectin; neuropilin 1 (212298_at; 210510_s_at); CD24; CD14; Cd163; CD53; Compliment Componenet 1-beta, 1-alpha, and 1-gamma; CDH4; integrin beta2; ADAM28; FK506 binding protein; collagen Valpha2; tumor necrosis factor receptor superfamily, member 6; tumor necrosis factor receptor superfamily, member 5; tumor necrosis factor (ligand) superfamily, member 13b; tumor necrosis factor receptor superfamily, member 12A; and the FGF receptor.

In another embodiment, there is provided a method of treating conventional or clear cell renal cell carcinoma. The method involves replacing tumor suppressor genes (e.g., via gene therapy) whose expression is down-regulated in tumor tissues or introducing a molecule that induces the down-regulated gene to be re-expressed in the tumor. The present invention discloses a number of genes that are down-regulated in stage I renal cell carcinoma (RCC), stage II RCC tumor, stage I papillary RCC, and benign oncocytoma. Some examples of down-regulated genes identified in stage I and/or II RCC tumors include, but are not limited to, CDKN1, secreted frizzled related protein 1, semaphoring 6D, semaphoring 3B, CDH16, TNF alpha, calbindin D28, defensin beta1, beta-catenin interacting protein 1, GAS1, vitamin D receptor, Kruppel-like factor 15. This method of treatment can be combined with other therapies to provide combinatorial therapy.

The genes that are found to have altered expression in stage I and stage II renal cell carcinoma would also be useful for determining patient prognosis. These genes or gene products (i.e., proteins) would have the unique characteristic of being altered in tumor verses normal samples in a subset of patients. For example, basic transcription element binding protein 1 is down-regulated in 7 out of 12 renal cell carcinoma tumors. Other examples include CD164, decreased 5/12; Map kinase kinase kinase 7, increased 6/12; Endoglin, increased 7/12; SERPIN A1, increased 6/12; Metalloprotease 11 (MMP11), increased 7/12; Integrin 3 alpha, increased 4/12; carbonic anhydrase II, decreased 7/12; protein tyrosine kinase 2, increased 4/12; fibroblast growth factor 11, increased 6/12; fibroblast growth factor 2, increased 7/12; VEGF B, increased 5/12.

Moreover, the levels of change may be a useful determinant of patient outcome and/or rationale for strategy of treatment course. An example of this is found for chemokine (C-X-C motif) ligand 14 (CXCL14, 222484_s_at). Six patients with stage I and six patients with stage II renal cell carcinoma were analyzed by genomic profiling. A patient with stage I renal cell carcinoma has CXCL14 mRNA expression levels of 19862 and 24.49 in his normal tissue and tumor tissue respectively. This patient would be predicted to have a poor prognosis or poor response to therapy based upon this result along with other gene predictors. On the other hand, a patient with stage II RCC has CXCL14 mRNA expression levels of 20435 and 18557 in his normal tissue and tumor tissue respectively. This patient would be predicted to have a good prognosis and good response to chemotherapy.

The following examples are given for illustrating various embodiments of the invention and are not meant to limit the present invention in any fashion. One skilled in the art will appreciate readily that the present invention is well adapted to carry out the objects and obtain the ends and advantages mentioned, as well as those objects, ends and advantages inherent herein. Changes therein and other uses which are encompassed within the spirit of the invention as defined by the scope of the claims will occur to those skilled in the art.

Example 1 Tissue Banking

Renal tissue (normal and tumor) was transported to a sterile hood on ice and under sterile conditions. Tissue was dissected under the direction of a pathologist. The tissue was frozen in liquid nitrogen for isolation of RNA, DNA, and protein or processed to establish primary cell cultures. The tissue was fixed in formalin for immunohistochemistry and in situ hybridization and RNAlater (Ambion) for RNA isolation. Primary normal renal epithelial (NRE) cell cultures were established using standard collagenase/Dnase techniques to digest tissue and isolate single cells. NREs were easily isolated and grew well in culture for up to 10 passages. These cells were further analyzed for homogeneity with regard to epithelial population using appropriate immunohistochemical markers such as vimentin, cytokeratin, and megalin.

Example 2 Genomic Gene Array and Microarray Data Analysis

Gene expression profiling was performed using Affymetrix HU95A oligonucleotide gene arrays (>12,600 genes) or HG-U133 A&B GeneChip® oligonucleotide microarrays (33,000+ probe sets). Total RNA (Trizol®, Ambion) was extracted from patient-matched normal renal cortex and tumor tissue from patients diagnosed with local disease confined to the kidney. Alternatively, the investigators analyzed metastatic disease defined by lesions in lymph nodes, adrenal, or other organs. Data were analyzed by a combination of two-dimensional ANOVA, Affymetrix MAS5.0®, and hierarchical cluster analysis using Spotfire®. Procedure that were used to identify altered expression of large sets of genes, as well as other issues concerning microarray analyses can be found in a recent review article by Copland et al. (2003).

Example 3 Real-Time PCR

Applied Biosystems' assays-by-design or assays-on-demand 20× assay mix of primers and TaqMan® MGB probes (FAM® dye-labeled) for all target genes and predeveloped 18S rRNA WIC® dye-labeled probe) TaqMan® assay reagent for internal control were used for real-time PCR measurements. These assays were designed to span exon-exon junctions so as not to detect genomic DNA and all primers and probes sequences were searched against the Celera database to confirm specificity. Validation experiments were performed to test the efficiency of the target amplification and the efficiency of the reference amplification. All absolute values of the slope of log input amount versus DC_(T) is less than 0.1.

Separate tubes (singleplex) for one-step RT-PCR was performed with 50 ng RNA for both target genes and endogenous controls using TaqMan® one-step RT-PCR master mix reagent kit (Applied Biosystems). The cycling parameters for one-step RT-PCR were: reverse transcription 48° C. for 30 min, AmpliTaq® activation 95° C. for 10 min, denaturation 95° C. for 15 s, and annealing/extension 60° C. for 1 min (repeat 40 times) on ABI7000®. Duplicate C_(T) values were analyzed with Microsoft Excel® using the comparative C_(T)(DDC_(T)) method as described by the manufacturer (Applied Biosystems). The amount of target (2^(−DDCT)) was obtained by normalizing to an endogenous reference (18smRNA) and relative to a calibrator (normal tissue).

Example 4 Immunohistochemical Analyses of Protein Expression

For immunohistochemical analyses of type I TGF-β receptor (TBR1), type II TGF-β receptor (TBR2), and type III TGF-β receptor (TBR3) expression, patient-matched normal renal and tumor tissue samples were fixed in 10% neutral-buffered formalin and embedded in paraffin blocks. Consecutive sections were cut 5 um thick, deparaffinized, hydrated, and immunostained using antibodies recognizing human TBR1, TBR2, and TBR3 (1:100; Santa Cruz Biotechnology). Biotinylated secondary antibody (1:600; Santa Cruz Biotechnology) was detected using avidin-biotin-peroxidase detection according to the manufacturer's instructions (Vectastatin Elite ABC kit; Vector Lab). All slides were lightly counterstained with hematoxylin before dehydration and mounting.

For cell lines, cells were plated on glass coverslips in wells. Prior to the detection of TGF-β receptor expression as described above, cells were fixed onto the coverslips with 3% formalin.

Example 5 Gene Expression Profiling of Renal Cell Carcinoma

Gene expression profiling was performed using Affymetrix oligonucleotide gene arrays. RNA was extracted from patient-matched normal renal cortical and tumor tissues from patients diagnosed with localized and metastatic renal cell carcinoma. Data were analyzed by a combination of two-dimensional ANOVA, Affymetrix MAS5.0®, and hierarchical cluster analysis using Spotfire® (reviewed in Copland et al., 2003).

A primary goal of microarray analysis is to discover hidden patterns of differential expression within a large data field. Normal renal cortical and primary tumor tissue with no metastasis were collected from patients diagnosed with local disease. Normal tissue, primary tumor, and metastatic tissue were also collected from patients diagnosed with metastatic disease. Comparison of patient-matched normal and tumor tissue allowed for the discovery of changes in mRNA levels between normal and tumor tissue, as well as local and metastatic disease.

Heatmaps with two-way dendograms depicting genes specifically altered in tumor tissue as compared to normal renal cortex are shown in FIG. 1. FIG. 1A shows hierarchical clustering of genes expressed in normal renal cortex verses stage I conventional renal cell carcinoma. FIG. 1B shows hierarchical clustering of genes expressed in normal renal cortex verses stage II renal cell carcinoma. FIG. 1C shows hierarchical clustering of genes selected from a Venn analysis in which the chosen genes were expressed in common in both stage I and II at a 99% confidence level.

TGF-β1, TGF-α and adrenomedulin mRNA levels were up-regulated in all stages of renal cell carcinoma as compared to normal tissue counterparts (FIGS. 2-4), whereas TGF-β2 and TGF-β3 mRNA levels were not altered between normal and tumor matched samples (FIGS. 5-6).

Tumor suppressor gene Wilms Tumor 1 (WT1) was down-regulated in all stages of renal cell carcinoma (FIG. 7). A small percentage of tumor tissues demonstrated attenuated von Hippel Lindau mRNA levels when compared to matched normal tissue (FIG. 8). Calbindin mRNA was completely lost (FIG. 9) while MUC1 was greatly attenuated in stage I renal cell carcinoma (FIG. 10).

The present analysis identifies 278 genes that were up-regulated in stage I renal cell carcinoma, whereas 380 genes were up-regulated in stage II renal cell carcinoma. Among these genes, 82 were up-regulated in both stages I and II renal cell carcinoma. One hundred fifty nine genes were down-regulated in stage I renal cell carcinoma, whereas 195 genes were down-regulated in stage II RCC. Among these genes, 82 were down-regulated in both stage I and II renal cell carcinoma.

Genes over-expressed and down-regulated in stage I renal cell carcinoma are listed in Table 1 and Table 2 respectively. Genes over-expressed and down-regulated in stage I renal cell carcinoma are listed in Table 3 and Table 4 respectively. Genes over-expressed in both stage I and II renal cell carcinoma are listed in Table 5. Genes down-regulated in both stage I and II renal cell carcinoma are listed in Table 6.

TABLE 1 Genes With Up-Regulated Expression In stage I Renal Cell Carcinoma Genbank ID Gene Symbol Genbank ID Gene Symbol NM004356.1 CD81 NM004079.1 CTSS NM002293.2 LAMC1 NM001784.1 CD97 NM000980.1 RPL18A AF151853.1 PREI3 AK002091.1 MGEA5 NM000491.2 C1QB NM005721.2 ACTR3 BC000125.1 TGFB1 NM002668.1 PLP2 NM004520.1 KIF2 NM021038.1 MBNL NM000321.1 RB1 AF070656.1 YME1L1 NM012262.2 HS2ST1 NM021029.1 RPL36A NM000560.1 CD53 NM002945.1 RPA1 NM005502.1 ABCA1 NM002480.1 PPP1R12A AF285167.1 ABCA1 NM001349.1 DARS BG170541 MET NM005496.1 SMC4L1 NM021642.1 FCGR2A AW163148 MARCKS BE967532 KIAA0220 NM002356.4 MARCKS NM006526.1 ZNF217 M68956.1 MARCKS NM000570.1 FCGR3B AI589086 LAPTM5 N26005 PPP1R3C NM006762.1 LAPTM5 NM006153.1 NCK1 NM014267.1 SMAP NM001549.1 IFIT4 NM000235.1 LIPA NM003141.1 SSA1 NM000176.1 NR3C1 NM014705.1 KIAA0716 NM005737.2 ARL7 NM005197.1 CHES1 NM005737.2 ARL7 NM002907.1 RECQL BC001051.1 ARL7 U43328.1 CRTL1 NM006169.1 NNMT NM017925.1 FLJ20686 NM005862.1 STAG1 NM006773.2 DDX18 AI356412 LYN U20350.1 CX3CR1 NM002350.1 LYN NM005761.1 PLXNC1 BG107456 TRIP-Br2 NM004834.1 MAP4K4 NM021913.1 AXL NM021644.1 HNRPH3 NM002194.2 INPP1 NM006640.1 MSF NM019058.1 RTP801 NM004180.1 TANK NM002110.1 HCK AW148801 NAP1L1 NM030755.1 TXNDC AB011118.1 KIAA0546 NM030984.1 TBXAS1 AU145005 SP3 NM014350.1 GG2-1 N80918 CG018 BC001312.1 P5 BF439472 ATP11A U14990.1 RPS3 BE968801 RPL35A D83043.1 HLA-B AI985751 NAP1L1 AI888672 NAP1L1 AI735692 LST1 BC002387.1 NAP1L1 AA995910 ALOX5 M60334.1 HLA-DRA M12679.1 HUMMHCW1A AF161522.1 C3orf4 AL133053.1 FLJ23861 BG256677 IFI16 X03348.1 NR3C1 M26880.1 UBC AC005339 N/A U17496.1 PSMB8 AK024836.1 HLA-C AF141347.1 TUBAS AC003999 SCAP2 L01639.1 CXCR4 AJ224869 CXCR4 NM005445.1 CSPG6 AL022067 PRDM1 AB030655.1 EFEMP2 AL110158.1 KIAA1078 AF165520.1 APOBEC3C S81916.1 N/A AF009670.1 ABCC3 M80469 N/A AF020314.1 CMRF-35H NM002860.1 PYCS BC001606.1 NCF2 NM020198.1 GK001 BC005352.1 GG2-1 NM016304.1 C15orf15 AF281030.1 HRIHFB2122 AA102574 BAZ1A BC001052.1 RECQL NM024844.1 PCNT1 L32610.1 HNRPH3 NM015938.1 CGI-07 M23612.1 RASA1 NM018200.1 HMG20A AF109683.1 LAIR1 NM025235.1 TNKS2 BC002841.1 HSA9761 NM015991.1 C1QA D29640.1 IQGAPI NM016090.1 RBM7 L25259.1 CD86 NM024554.1 PGBD5 M60333.1 HLA-DRA NM017718.1 FLJ20220 U13698.1 CASP1 NM017923.1 FLJ20668 U90940.1 FCGR2C NM030921.1 DC42 M90685.1 HLA-G BC004470.1 ASC M90684.1 HLA-G AK021413.1 LARS M90686.1 HLA-G BF444916 FAD104 L22453.1 RPL3 BC004819.1 PLDN U01351.1 NR3C1 AF247167.1 AD031 U62824.1 HLA-C U39402.1 N/A L07950.1 HLA-B BC006112.1 DKFZP434B195 AF348491.1 CXCR4 BG388615 N/A NM003079.1 SMARCEI AB033007.1 KIAA1181 BE646386 EXO70 BG250721 N/A A1972475 N/A AK024221.1 C40 AA195999 MAPK1 BF477658 N/A AL049397.1 N/A BG251556 KIAA1949 BE895685 KIAA0853 AB033091.1 KIAA1265 M82882.1 ELF1 AK024350.1 AMOTLI AB020633.1 KIAA0826 NM018440.1 PAG AL031781 N/A AW500180 N/A BF209337 MGC4677 AW026543 N/A AI709406 N/A AI092770 N/A AI806905 N/A NM020679.1 AD023 AI392933 FLJ36090 AK024855.1 CTSS AI142096 N/A AK000119.1 N/A AL137430.1 N/A AW977527 PRDM1 AV724266 FLJ20093 BE671060 N/A BF589359 N/A AL037450 N/A AW084125 CAPZA1 AI401535 N/A N20927 RAP2B AV683852 N/A AI627666 LOC115548 BF055144 N/A AV726322 N/A AA352113 N/A AI697657 LANPL BF056209 N/A BF002625 N/A X60592 TNFRSF5 BF439533 N/A

TABLE 2 Genes With Down-Regulated Expression In stage I Renal Cell Carcinoma Genbank ID Gene Symbol L38487 ESRRA NM004415.1 DSP NM005327.1 HADHSC NM003321.1 TUFM NM002084.2 GPX3 AI983043 N/A NM006066.1 AKR1A1 NM006384.2 CIB1 NM001685.1 ATP5J NM014652.1 IMP13 NM013410.1 AK3 NM016725.1 FOLR1 NM021151.1 CROT NM005951.1 MT1H NM005952.1 MT1X AL080102.1 N/A BC000931.2 ATP5C1 BC005398.1 DKFZP566D193 D87292.1 TST AU151428 IDH2 BC000109.1 ILVBL AF333388.1 N/A NM005953.1 MT2A BF217861 N/A AA594937 COBL AW052179 COL4A5 AI884867 LOC155066 BF246115 N/A AW028110 KIAA0500 AW242315 N/A AW080549 FUT3 AW149846 GPX3 AI038402 N/A AI051046 MGC4614 AI659456 N/A AW664964 N/A AI631895 SGK2 AI263078 FLJ31168 BF057634 HOXD8 AA746038 GPR110 AK024386.1 GRHPR AL109716.2 N/A AK026411.1 ALDOB M10943 N/A AW088547 N/A NM018049.1 GNRPX NM017900.1 AKIP NM006548.1 IMP-2 NM025135.1 KIAA1695 NM016458.2 LOC51236 NM022128.1 RBSK NM015974.1 CRYL1 NM013333.1 EPN1 AA133341 C14orf87 AF226732.1 NPD007 AF265439.1 MRPS15 AI743534 DKFZP564B1162 AB042647.1 B29 AL522667 ORF1-FL49 BG255416 KIAA0114 AF308301.1 MRPS26 BE408081 N/A AL521634 FLJ32452 BF203664 MGC14288 BE645551 MGC39329 AW193698 TGFBR3 BF540829 N/A W72455 FLJ25476 AI457453 N/A BF056892 N/A AK024386.1 GRHPR AL109716.2 N/A AA442776 N/A AI913600 N/A AW771908 N/A AI807887 N/A AW102941 N/A AW024656 N/A AB002342 PRKWNK1

TABLE 3 Genes With Up-Regulated Expression In stage II Renal Cell Carcinoma Genbank ID Gene Symbol NM006096.1 NDRG1 NM006098.1 GNB2L1 NM001780.1 CD63 NM003118.1 SPARC NM000291.1 PGK1 NM003870.1 IQGAP1 AB032261.1 SCD NM002629.1 PGAM1 NM003564.1 TAGLN2 NM000310.1 PPT1 NM003405.1 YWHAH U82164.1 MIC2 NM002305.2 LGALS1 NM001096.1 ACLY NM002121.1 HLA-DPB1 NM021038.1 MBNL NM003651.1 CSDA AV685920 CAPZA2 NM002654.1 PKM2 NM001175.1 ARHGDIB BC000182.1 ANXA4 NM001153.2 ANXA4 NM001975.1 ENO2 NM006435.1 IFITM2 NM001387.1 DPYSL3 BG398414 RPA1 NM004039.1 ANXA2 NM005534.1 IFNGR2 AL136877.1 SMC4L1 NM014876.1 KIAA0063 NM024830.1 FLJ12443 NM005505.1 SCARB1 NM003025.1 SH3GL1 NM013285.1 HUMAUANTIG NM005720.1 ARPC1B AW157070 EGFR NM002835.1 PTPN12 NM004428.1 EFNA1 AW006290 SUDD NM014791.1 MELK NM014882.1 KIAA0053 NM003864.1 SAP30 NM001558.1 IL10RA NM003264.1 TLR2 NM014221.1 MTCP1 AV756141 CSF2RB AI123251 LCP2 NM006433.2 GNLY NM000861.2 HRH1 NM001870.1 CPA3 NM003586.1 DOC2A NM004271.1 MD-1 NM014932.1 NLGN1 NM014947.1 KIAA1041 NM000647.2 CCR2 NM002562.1 P2RX7 NM006058.1 TNIP1 NM013447.1 EMR2 NM013416.1 NCF4 NM001776.1 ENTPD1 NM020037.1 ABCC3 NM006135.1 CAPZA1 NM007036.2 ESM1 AF034607.1 CLIC1 BC000915.1 PDLIM1 AL162068.1 NAP1L1 NM006947.1 SRP72 L12387.1 SRI AF141349.1 N/A AF263293.1 SH3GLB1 BC000389.1 TM4SF7 AF007162.1 CRYAB D38616.1 PHKA2 AV717590 ENTPD1 U87967.1 ENTPD1 H23979 MOX2 AF063591.1 MOX2 BC005254.1 CLECSF2 BC000893.1 H2BFT L22431.1 VLDLR AI741056 SELPLG AF084462.1 RIT1 U62027.1 C3AR1 M87507.1 CASP1 J04132.1 CD3Z M31159.1 IGFBP3 AF257318.1 SH3GLB1 BC001388.1 ANXA2 AF130095.1 FN1 AF022375.1 VEGF AA807529 MCM5 AK026737.1 FN1 X14355.1 N/A AK025608.1 KIAA0930 AF183421.1 RAB31 NM002695.1 POLR2E AF288391.1 C1orf24 NM003730.2 RNASE6PL NM016359.1 ANKT NM014164.2 FXYD5 NM022736.1 FLJ14153 NM021158.1 C20orf97 NM017792.1 FLJ20373 NM020142.1 LOC56901 NM016448.1 RAMP NM005767.1 P2Y5 NM020169.1 LXN NM022834.1 FLJ22215 NM018460.1 BM046 NM024629.1 FLJ23468 NM018641.1 C4S-2 NM018295.1 FLJ11000 NM024576.1 FLJ21079 NM016582.1 PHT2 NM003116.1 SPAG4 NM018454.1 ANKT NM018099.1 FLJ10462 NM007072.1 HHLA2 NM022445.1 TPK1 AW173623 TDE1 AB044088.1 BHLHB3 AF043244.1 NOL3 AF133207.1 H11 AF313468.1 CLECSF12 AA191576 NPM1 AI765383 KIAA1466 BC003654.1 SLC27A3 W60806 N/A AI335263 NETO2 AI378406 EGLN3 BC005400.1 FKSG14 AI761520 CENTA2 BC000771.1 TPM3 BC000190.1 HSPC216 BC002776.1 SEMA5B AF132203.1 SCD BC006107.1 ARHGAP9 AK024263.1 N/A AK024846.1 SET7 BE878463 N/A AW304786 PTR4 AI769269 N/A AI935334 N/A BF437747 SAMHD1 AW300953 N/A H37811 N/A AA603344 SAMHD1 AA742310 N/A AI248208 FLJ25804 AI962367 ECGF1 NM002053.1 GBP1 NM000089.1 COL1A2 NM021105.1 PLSCR1 NM002467.1 MYC NM001284.1 AP3S1 AI825926 PLSCR1 NM014736.1 KIAA0101 AF161461.1 LEPROTL1 NM014873.1 KIAA0205 AI005043 N/A NM000416.1 IFNGR1 NM004172.1 SLC1A3 NM004207.1 SLC16A3 AI761561 HK2 Y09216.1 N/A NM002922.1 RGS1 NM005990.1 STK10 NM014863.1 GALNAC4S-6ST NM014737.1 RASSF2 NM000418.1 IL4R BC000658.1 STC2 NM003751.1 EIF3S9 NM002339.1 LSP1 NM004604.1 STX4A NM006404.1 PROCR AF275945.1 EVA1 NM004221.1 NK4 NM004556.1 NFKBIE NM004688.1 NM NM003332.1 TYROBP NM015136.1 STAB1 NM006019.1 TCIRG1 NM004877.1 GMFG NM002317.1 LOX NM025201.1 PP1628 NM014800.1 ELMO1 L41944.1 IFNAR2 NM007268.1 Z39IG NM006994.2 BTN3A3 AF091352.1 VEGF AB035482.1 ICB-1 Z24727.1 TPM1 M19267.1 TPM1 U13700.1 CASP1 M27281.1 VEGF BC005838.1 N/A BC005858.1 FN1 BC005926.1 EVI2B BE513104 YARS AU147399 CAV1 AK023154.1 HN1L AK021757.1 KIAA0648 H95344 VEGF AB023231.1 FNBP4 AL523076 N/A NM030666.1 SERPINB1 AB018289.1 KIAA0746 AW043713 SULF1 BE880591 EP400 AU158495 NOTCH2 BE965029 N/A AL564683 CEBPB AA349595 RAB6IP1 AI809341 PTPRC AW205215 KIAA0286 BE349017 HA-1 AF070592.1 HSKM-B AI769685 CARS AI935123 LOC113146 BG255188 N/A AI088622 PRKCDBP BE222709 N/A AW007573 DKFZP586L151 BG332462 N/A AI862658 FEM1C AI934469 KIAA0779 AB018345.1 KIAA0802 W87466 LOC92689 BE908217 ANXA2 NM005615.1 RNASE6 BE300252 K-ALPHA-1 BF740152 MYO1F AV711904 LYZ AW072388 N/A AW190316 SHMT2 NM005412.1 SHMT2 NM006417.1 IFI44 AL008730 C6orf4 L16895 LOC114990 Z21533.1 HHEX AK022955.1 DKFZp762L0311 BF001267 N/A AL558987 N/A AA577672 LOC151636 BE620734 ZAK AI937446 N/A H99792 N/A BE966748 N/A AI659418 MGC21854 AI990891 DKFZp761K2222 AA827892 N/A AL135264 N/A AI375753 N/A AA573502 TAP2 BG387557 CASP2 AA554833 MAP1B AK026764.1 N/A AU146532 PDK1 BE348597 N/A AL577758 LOC133957 AI133452 FGG AU157224 N/A AI742057 N/A BE500942 N/A N25631 RFXANK AU145366 N/A AW270037 KIAA0779 BF526978 N/A AW182575 N/A BF339831 MGC13114 AI056992 N/A BE222668 N/A BG165011 N/A AI188445 MGC14289 BE551416 HAK AI972498 a1/3GTP AW662189 N/A AA142842 N/A BF939473 N/A AI681260 N/A AA551090 AP1S2 AA045175 MS4A6A W05495 N/A AI093231 N/A AI565054 N/A AL553774 N/A AK023470.1 MGC15875 AL157377 ENPP3 AL139109 TEX11 AK025631.1 POLH AI873425 N/A BF541967 N/A AI686890 N/A AI936034 ITGA4 U88964 ISG20 AJ243797 TREX1 D29642 KIAA0053 D87433 STAB1 AI129310 FLJ21562

TABLE 4 Genes With Down-Regulated Expression In stage II Renal Cell Carcinoma Genbank ID Gene Symbol NM012248.1 SPS2 NM002300.1 LDHB BC000306.1 HADHSC NM001640.2 APEH NM005875.1 GC20 NM003365.1 UQCRC1 BF031714 HYA22 NM005808.1 HYA22 AF113129.1 ATP6V1A1 NM002402.1 MEST NM006844.1 ILVBL NM004636.1 SEMA3B NM002496.1 NDUFS8 NM006556.1 PMVK NM004255.1 COX5A NM002225.2 IVD NM004524.1 LLGL2 AI950380 BCL7A AB020707.1 WASF3 NM000481.1 AMT NM012317.1 LDOC1 NM006456.1 STHM NM006614.1 CHL1 NM015393.1 DKFZP564O0823 AV729634 DNAJC6 NM002628.1 PFN2 NM003500.1 ACOX2 NM002655.1 PLAG1 NM004393.1 DAG1 NM003026.1 SH3GL2 NM002010.1 FGF9 NM014033.1 DKFZP586A0522 NM004868.1 GPSN2 BC000649.1 UQCRFS1 S69189.1 ACOX1 AF153330.1 SLC19A2 AF094518.1 ESRRG M55575.1 BCKDHB BE044480 MGC32124 BF382393 N/A AV751731 PNKP U55984 N/A BF059512 DNER AK025934.1 Evi1 AL036088 SEMA6D BE964222 FLJ38482 AW290940 N/A AL545998 N/A AW274874 N/A AI709389 N/A BF224092 MGC15854 AU145805 N/A AW079843 MGC33338 AW138815 N/A AW242286 N/A AW025023 N/A BE672659 N/A AB019695.1 TXNRD2 M61900.1 PTGDS BF967998 N/A BF967998 N/A AL526243 KIAA0446 NM000532.1 PCCB BE042354 LDHB AI587323 ATP5A1 AW195882 ATPW H71135 ADH6 AV659180 ALDOB AK027006.1 TNRC9 AV693216 PLXNB1 BG398937 N/A NM002489.1 NDUFA4 NM003849.1 SUCLG1 NM014019.1 HSPC009 NM024952.1 FLJ20950 NM014185.1 MOG1 NM018013.1 FLJ10159 NM018373.1 SYNJ2BP NM014067.2 LRP16 NM013261.1 PPARGC1 NM021963.1 NAP1L2 NM018658.1 KCNJ16 NM014553.1 LBP-9 AF112204.1 ATP6V1H AU145941 CDC14B AF061264.1 MGC4825 BF941492 FLJ10496 AI984229 HSPC121 N71923 FLRT3 BC005050.1 NICN1 AF172327.1 N/A AF356515.1 HINT2 BE620739 RHOBTB3 BF435123 N/A AW149498 BTBD6 AW024437 LOC118491 AW195353 N/A BE044193 N/A AI493303 FLJ31709 AI636080 N/A BF509031 ATP6V1G3 AW242920 N/A BF002046 ANGPTL1 BF130943 N/A AW452631 N/A AI792937 N/A AI810572 N/A BG165743 LOC112817 AW466989 N/A R48991 N/A BF029215 MSI2 D21851 LARS2 Z83838 ARHGAP8

TABLE 5 Genes With Up-Regulated Expression In both stage I & stage II Renal Cell Carcinoma Genbank ID Gene Symbol NM005566.1 LDHA NM000291.1 PGK1 NM001219.2 CALU NM002966.1 S100A10 NM000034.1 ALDOA NM002627.1 PFKP NM006082.1 K-ALPHA-1 AI922599 VIM NM020474.2 GALNT1 NM006406.1 PRDX4 NM015344.1 LEPROTL1 NM014755.1 TRIP-Br2 AI796269 NBS1 NM005783.1 APACD BF197655 N/A NM001233.1 CAV2 NM002845.1 PTPRM NM014302.1 SEC61G U47924 CD4 NM004106.1 FCER1G NM015474.1 SAMHD1 NM004915.2 ABCG1 NM002432.1 MNDA NM005565.2 LCP2 NM005531.1 IFI16 NM005849.1 IGSF6 NM002189.1 IL15RA NM004353.1 SERPINH1 NM017760.1 FLJ20311 NM022349.1 MS4A6A NM023003.1 TM6SF1 NM016184.1 CLECSF6 NM031284.1 DKFZP434B195 BC002342.1 CORO1C AA775177 PTPRE AL162070.1 CORO1C AF253977.1 MS4A6A AF237908.1 MS4A6A W03103 DDEF1 AK022888.1 FENS-1 AI141784 N/A NM014812.1 KIAA0470 AF208043.1 IFI16 BC002654.1 TUBB-5 BC006379.1 K-ALPHA-1 BC006481.1 K-ALPHA-1 AF000426.1 LST1 AF000424.1 LST1 BG500301 ITGB1 AL516350 ARPC5 M27487.1 HLA-DPA1 M27487.1 HLA-DPA1 AW517686 ATP2B4 AL581768 K-ALPHA-1 AA524505 TSGA Z78330 ACTR3 Z78330 ACTR3 BG532690 ITGA4 AW005535 RAP2B NM007161.1 LST1 AK026577.1 ALDOA AI091079 SHC1 AV713720 LST1 NM021103.1 TMSB10 NM016337.1 RNB6 NM013260.1 HCNGP NM021199.1 SQRDL NM018149.1 FLJ10587 NM016951.2 CKLF1 AB033038.1 FLJ10392 AI184968 C1QG AL161725 FLJ00026 NM018440.1 PAG AL553942 FLJ31951 AI394438 N/A T64884 N/A T64884 N/A AW511319 N/A AI640834 RA-GEF-2 AI655467 N/A AL161725 FLJ00026 T92908 N/A

TABLE 6 Genes With Down-Regulated Expression In Both stage I And stage II Renal Cell Carcinoma Genbank ID Gene Symbol NM004092.2 ECHS1 NM000270.1 NP NM002354.1 TACSTD1 AF017987.1 SFRP1 NM003012.2 SFRP1 NM000666.1 ACY1 NM000191.1 HMGCL NM015254.1 KIF13B NM000140.1 FECH U75667.1 ARG2 NM000196.1 HSD11B2 NM014636.1 RALGPS1A NM001441.1 FAAH NM005978.2 S100A2 NM001678.1 ATP1B2 NM001099.2 ACPP NM014731.1 ProSAPiP1 BF343007 N/A NM000035.1 ALDOB NM005950.1 MT1G NM002371.2 MAL NM006984.1 CLDN10 NM002567.1 PBP NM000019.1 ACAT1 NM001692.1 ATP6V1B1 X77737.1 N/A NM006226.1 PLCL1 NM000893.1 KNG NM000412.2 HRG NM001963.2 EGF NM003361.1 UMOD NM000050.1 ASS NM001438.1 ESRRG NM020632.1 ATP6V0A4 AI632015 SLC12A1 NM000701.1 ATP1A1 NM031305.1 DKFZP564B1162 AF130089.1 ALDH6A1 AK025651.1 N/A W45551 MMP24 W67995 FXC1 AL136566.1 IBA2 AF105366.1 SLC12A6 AF284225.1 DMRT2 AA191708 N/A AL355708.1 N/A BE783949 FLJ10101 AL529672 N/A AL568674 MYBBP1A AU147564 CLMN AK000208.1 N/A AB051536.1 FLJ14957 AI569747 TFDP2 AK025562.1 N/A AI660243 TMPRSS2 N50413 N/A AI347918 N/A AL536553 GRP58 BC000282.1 LOC89894 BF106962 FAM3B AI051248 FLJ32115 AI928242 N/A BG236006 N/A AI653107 N/A AI824037 FLJ25461 R61322 N/A AW071744 KCNJ10 BF059276 N/A BC002449.1 FLJ13612 J02639.1 SERPINA5 BC002571.1 DKFZP564O243 U03884.1 KCNJ1 AF173154.1 HYAL1 AF130103.1 PBP AL117618.1 PDHB AF063606.1 N/A BC005314.1 N/A BF686267 PBP AI742553 PRKWNK1 D83782.1 SCAP AB029031.1 TBC1D1 AK025432.1 KIAA0564 AL117643.1 N/A AW772192 N/A NM003944.1 SELENBP1 AL049977.1 CLDN8 AK023937.1 THEA AK025084.1 TNRC9 X03363.1 ERBB2 AK026411.1 ALDOB NM016026.1 RDH11 NM016286.1 DCXR NM019027.1 FLJ20273 BG338251 RAB7L1 NM006113.2 VAV3 NM018075.1 FLJ10375 NM013271.1 PCSK1N NM017586.1 C9orf7 NM016321.1 RHCG NM025247.1 MGC5601 BC002449.1 FLJ13612 AI379517 N/A AA058832 MGC33926 AW274034 N/A AI580268 NUDT6 AI761947 DKFZP564B1162 AI793201 N/A AK025898.1 N/A AB046810.1 C20orf23 AK024204.1 N/A BF594722 N/A R88990 N/A N73742 N/A AI697028 FLJ90165 BF590528 N/A AI733359 N/A H20179 N/A AA991551 MGC14839 AI758950 SLC26A7 AA911561 N/A AI769774 N/A AA669135 N/A AW136060 SLC13A2 AI733593 N/A BF739841 N/A AA600175 N/A BF477980 N/A AI934557 N/A BE326951 KNG AI632567 N/A BE300882 N/A BE855713 N/A AA485440 DBP AA915989 FLJ10743 AA085764 SIGIRR

Example 6 Loss of TGF-β Receptor Expression Demonstrated by Gene Array and Real-Time PCR in Renal Cell Carcinoma

Expression of type I TGF-β receptor (TBR1), type II TGF-β receptor (TBR2), and type III TGF-β receptor (TBR3) mRNA were compared in normal renal tissue, primary renal cell carcinoma without metastasis, primary lesions of metastatic renal cell carcinoma, and metastatic lesions. A summary of gene array analysis was presented as average signal intensities in FIG. 11A (mean±standard error). The signal intensity for TBR1 (cross-hatched bars) was relatively low, although TBR1 was scored as ‘Present’ in all samples. No significant changes in TBR1 expression were observed. TBR2 (gray bars) was abundantly expressed in normal epithelium and in primary lesions of nonmetastatic renal cell carcinoma. TBR2 was significantly reduced in primary lesions with metastatic disease (P<0.028 by ANOVA). TBR2 was even more reduced in metastatic lesions. TBR3 expression was high in normal epithelium, but was significantly reduced in each of the five primary tumors with nonmetastatic disease (black bars). TBR3 expression was also reduced in primary tumors with metastatic lesions and in metastatic lesions themselves.

These expression patterns were confirmed by real-time PCR (Tagman®) in the 10 patients used for gene array analysis. Means and standard errors for individual samples are shown in FIG. 11B. All data were normalized to 18S rRNA and calibrated to target abundance in the paired normal tissues. TBR1 mRNA abundance did not change (cross-hatched bars), consistent with the gene chip data. TBR2 (gray bars) was not reduced in primary tumors without metastases, whereas TBR2 was significantly reduced in primary tumors with metastatic disease and in metastatic lesions. TBR3 was reduced in all tumors (black bars).

The investigators have subsequently completed real-time PCR analysis of TBR1, TBR2, and TBR3 expression in 16 primary tumors without metastases (plus paired normal epithelium) and nine samples of primary tumors with metastatic disease, paired metastatic lesions, and paired normal tissue. The data were consistent with those shown for the samples analyzed in FIG. 11A. TBR3 expression was significantly reduced in all tumors; whereas TBR2 expression was reduced in only 1/16 primary tumors without metastatic lesions, but was reduced in primary tumors with metastatic lesions (8/9). These data show that loss of TBR3 is an early event in renal cell carcinoma, strongly suggesting that TBR3 plays a critical role in renal cell carcinoma carcinogenesis.

The loss of TBR3 mRNA expression was also correlated with TNM scores (T, histological score; N, lymph node number; M, number of organ metastases) from patient samples (data not shown). TBR3 mRNA expression was suppressed in the earliest stage, stage I, and was found to be suppressed in all tumor stages (I-IV). In addition, loss of TBR2 in the primary tumor is significantly associated with acquisition of the metastatic phenotype and clinically manifests as metastatic progression.

Example 7 Attenuation of TGF-β-Mediated Signal Transduction In Human Renal Cell Carcinoma

Decreased type III TGF-β receptor (TBR3) mRNA expression in all tumors was associated with failure to detect TBR3 protein by immunohistochemistry (FIG. 12). Type I TGF-β receptor (TBR2) protein was detected in localized tumor (primary, no mets), but was not detectable in primary tumors with metastatic disease or in corresponding metastatic lesions. Type I TGF-β receptor (TBR1) protein was detected in normal tissue and in all tumor samples.

The investigators hypothesized that these losses seen in TGF-β receptor expression would manifest as an attenuation of TGF-β mediated signal transduction, and would significantly alter the expression of TGF-β regulated genes. From the gene array data disclosed above, 13 known TGF-3/Smad-regulated genes were down-regulated in renal cell carcinoma (Table 7). Using mRNA from 35 patient-matched samples, the investigators verified loss of expression of three of these genes by comparing matched normal and tumor tissue. Real-time PCR was used to measure the expression of Collagen IV type 6, fibulin-5, and connective-tissue growth factor (CTGF). Collagen IV type 6 (gray bars) is an extracellular matrix protein that plays a critical role in the regulation of membrane integrity and cell signaling. Fibulin-5 is a recently discovered TGF-3-regulated gene, which has tumor suppressor activity. Fibulin-5 is an extracellular matrix protein that is believed to signal through interaction with integrins. CTGF is a secreted protein involved in angiogenesis, skeletogenesis, and wound healing. CTGF enhances TGF-β1 binding to TBR2, and CTGF and TGF-β collaborate to regulate the expression of extracellular matrix proteins during renal fibrosis. As summarized graphically in FIG. 13, all the evaluated TGF-β-regulated genes were down-regulated in early tumor stages, suggesting that renal cell carcinoma undergoes loss of TGF-β responsiveness at an early stage. These data indicate that this loss of TGF-β sensitivity is due, primarily, to loss of type III TGF-β receptor (TBR3) in early tumor development and further loss of sensitivity in metastatic disease is mediated through subsequent loss of type II TGF-β receptor (TBR2).

TABLE 7 Known TGF-β-Regulated Genes Found To Be Down- Regulated In Localized Tumors By Gene Array Analysis Fold GenBank No. Gene Name Attenuation S81439 TGFβ-induced early growth factor 2.5 (TIEG) AF093118 Fibulin 5 4.0 U42408 Ladinin 1 15.4 U01244 Fibulin 1 4.8 J05257 Dipeptidase 1 7.7 D21337 Collagen, type IV, a6 3.6 X80031 Collagen, type IV, a3 2.4 M64108 Collagen, type XIV, a1 3.2 M98399 Collagen, type I receptor 4.2 L23808 Matrix metallo-proteinase 12 3.7 M35999 Integrin, b3 2.5 AI304854 p27^(Kip1) 2.1 J05581 Mucin 1 6.5 Data were analysed by a combination of two-dimensional ANOVA, Affymetrix MAS5.0, and hierarchical cluster analysis using Spotfire to identify genes that are down-regulated in local tumors versus that of normal renal cortex tissue.

Example 8

TGF-β Receptor Expression in Renal Cell Carcinoma Cell Lines

Human renal cell carcinoma cell lines were identified that recapitulate the clinical observations of TGF-β receptor biology described above. UMRC6 cells were derived from a clinically localized human renal cell carcinoma (Grossman et al., 1985). As shown in FIG. 14A, UMRC6 cells express type II TGF-β receptor (TBR2) mRNA, but not type III TGF-β receptor (TBR3). Immunohistochemical analysis (FIG. 14B) confirms the presence of TBR2 protein and the absence of TBR3 expression. UMRC3 cells were derived from the primary tumor of a patient with metastatic renal cell carcinoma. This highly aggressive cell line lacks detectable TBR2 and TBR3 mRNA (FIG. 14A) and protein (FIG. 14B).

In addition to these relevant laboratory models, normal renal epithelial (NRE) tissue was harvested from nephrectomy specimens and established as primary cultures

(Trifillis, 1999). As shown in FIGS. 14A and 14B, these primary cultures of NRE expressed TBR3, TBR2, and TBR1 mRNA and protein in vitro. NRE cells can be grown in culture for 10 passages and were easily isolated and characterized. NRE cells were characterized for cytokeratin expression and tubule-specific gene expression, for example, megalin (data not shown). Thus, there are relevant cell models in which TBR2 and TBR3 expression can be manipulated to examine the impact of TGF-β receptor biology on the carcinogenesis and progression of human renal cell carcinoma in vitro.

Example 9

TGF-β Activity In Renal Cell Carcinoma Cell Lines

It is well known that TGF-β1 inhibits cell proliferation in epithelial cells. The present example demonstrates the effects of TGF-β on renal tumor cell proliferation. DNA content of cells was used as a measure of cell proliferation. Cells were plated at 20,000 cells/well in 12-well plates. Cells were grown in 10% FBS:DMEM:penicillin:streptomycin. The following day, media were exchanged with appropriate treatment added to the media. On day 3 of treatment, cells were analyzed for DNA content using Hoechst reagent. DNA standard was used to correlate DNA content per well. As shown in FIG. 15A (squares), TGF-β1 inhibited the proliferation of normal renal epithelial cells in culture. URMC3 cells expressed neither type II or type III TGF-t3 receptors and, not surprisingly, were resistant to the inhibitory effects of TGF-β on cell proliferation (triangles, FIG. 15A). UMRC6 cells expressed type II but not type III TGF-β receptors, and were partially resistant to TGF-β1 (circles, FIG. 15A).

TGF-β transcriptional activity was also measured in the above cell models using transient transfection of the 3TP/lux reporter, which contains an AP-1/Smad3 response element from the PAI-1 promoter. This luciferase reporter construct demonstrates increased transcriptional activity in response to exogenous TGF-β-mediated signal transduction. 3TP/lux was transiently transfected along with SV/renilla luciferase (Promega) into cells using fugene (Roche) as the transfection agent. Cells were treated with or without TGF-β1 24 h after transfection and luciferase activity (Promega Luciferase Assay system and Lumat luminometer) was determined 24 h after TGF-β treatment. Firefly luciferase activity was normalized using the ratio of firefly luciferase/renilla luciferase. As shown in FIG. 15B, normal renal epithelial cells were highly responsive to 2 ng/ml (80 pM) of TGF-β1. UMRC6 cells demonstrated significantly less luciferase activity in response to TGF-β1, and UMRC3 cells were entirely unresponsive.

Example 10

Recapitulation of TGF-β Signaling Through Reintroduction of TGF-b Receptor Expression into Renal Cell Carcinoma

To test whether reintroduction of TGF-β receptor expression would result in re-establishment of TGF-β signal transduction and reacquisition of TGF-β cellular sensitivity, UMRC3 cells were engineered to express stably either type II TGF-β receptor (+TBR2) alone or type II plus type III TGF-β eceptor (+TBR2+TBR3).

Plasmid construction and transfection were described as follows. The complete coding sequences for human type II TGF-β receptor (TBR2) was cloned into the EcoRI/XbaI site of pcDNA3/FLAG. The expression vector was stably transfected into UMRC3 cells using fugene as DNA carrier and genticin as selection antibiotic (Sigma, 1 mg/ml). Ten clones (UMRC3/TBR2) were selected and verified for TBR 2 mRNA and protein expression such as Western analysis using the FLAG antibody (data not shown). From these cell clones, one was to be selected that had equivalent protein expression of TBR2 to that of normal renal epithelial (NRE) and UMRC6 cells.

The type III TGF-β receptor (TBR3) coding sequence was PCR amplified from a plasmid expressing wild-type TBR3 in pSV7d (a gift from Dr C-H Heldin). TBR3 was then cloned into the EcoRI site of pcDNA4/TO/myc-His® (InVitrogen) in the sense and antisense (negative control) orientation. The orientation and sequence of TBR3 was verified. The antisense TBR3 (As TBR3) vector was used as a control. TBR3/pcDNA4/TO/myc-His and As TBR3/pcDNA4/TO/myc-His vectors were stably transfected into UMRC3/TBR2 cells. A clone was selected that demonstrated an equivalent expression of TBR3 mRNA to that of normal renal epithelial cells. As a control for UMRC3+TBR2 and UMRC3+TBR2+TBR3, wild-type UMRC3 were stably transfected with both pcDNA/FLAG and pcDNA4/TO/myc-His vectors.

As shown in FIGS. 16A-16B, stable transfection of type II TGF-β receptor (TBR2) alone or type II plus type III TGF-β receptor (TBR2+TBR3) resulted in detectable levels of mRNA for each receptor on RT-PCR analysis. On examining the in vitro growth kinetics of these re-engineered cells, it was noted that reintroduction of TBR2 resulted in a twofold reduction in cell proliferation and reintroduction of both TBR2 and TBR3 resulted in a fourfold reduction in cell proliferation with the addition of exogenous TGF-3.

The investigators then examined TGF-13-mediated transcriptional activity as a consequence of TGF-β receptor re-expression. As shown in FIG. 16C, reintroduction of TBR2 partially restored transcriptional responsiveness, as evidenced by a 5.6-fold increase in 3TP/lux activity after addition of TGF-β1. Reintroduction of both TBR2 and TBR3 into UMRC3 cells resulted in 17.5-fold increase in 3TP/lux activity after addition of TGF-β1.

To demonstrate reestablishment of TGF-β-regulated gene expression, collagen IV type 6 mRNA expression was examined by real-time PCR in these re-engineered cell lines in the presence of TGF-β1. As shown in FIG. 16D, reexpression of TBR2 in UMRC3 cells results in a sevenfold increase in collagen IV type 6 mRNA levels over that of UMRC3 controls, while reintroduction of both TBR2 and TBR3 enhanced collagen IV type 6 mRNA expression 11-fold. These data are consistent with a number of published reports that indicate expression of TBR3 is essential for full TGF-β responsiveness.

UMRC3 cells have been shown to be tumorigenic in athymic nude mice (Grossman et al., 1985). Anchorage independent growth in soft agar is a well-established in vitro correlate of in vivo tumorigenicity. Colonies formation in soft agar was determined as follows. UMRC3 (pcDNA/FLAG and pcDNA4/T0/myc-His empty vectors), UMRC3+TBR2, or UMRC3+TBR2+TBR3 cells were plated at 1000 cells/60 mm dish in an agarose/FBS/media sandwich in the presence of 2 ng/ml TGF-β. No selection antibodies were added to the agarose media mixture. The cells were incubated for 45 days to insure that no colony formation would occur. Cells were then stained with 0.005% Crystal Violet, photographed, and assessed for number and size of colonies.

As shown in FIG. 16E, UMRC3 cells demonstrated anchorage independent growth in soft agar. Reintroduction of TBR2 into UMRC3 cells significantly decreased the number and size of colonies that formed in soft agar. Reintroduction of both TBR2 and TBR3 completely abrogated the ability of UMRC3 cells to form colonies in soft agar, even after 45 days in culture. These data demonstrate that reintroduction of TBR2 resensitizes UMRC3 cells to the effects of exogenous TGF-β through reacquisition of TGF-β signal transduction. More interestingly, however, reintroduction of TBR3 in the presence of TBR2 into UMRC3 cells significantly enhanced TGF-β-regulated gene transcription, growth inhibition, and loss of anchorage-independent growth over that seen with reintroduction of TBR2 alone. These data clearly show that renal cell carcinoma cells are TGF-β resistant. Loss of TBR3 expression occurs early and appears to be associated with a relatively less aggressive state that is partially TGF-β responsive. Loss of TBR2 results in frank TGF-β resistance and is associated with acquisition of a more aggressive phenotype.

FIGS. 17-18 demonstrate that re-expression of type II or type III TGF-β receptor in the highly metastatic human renal cell carcinoma cell line UMRC3 inhibited cell proliferation in cell culture and tumor growth in a nude mouse model. The TGF-β receptors were either re-expressed in a stable vector system or as an adenoviral vector. For clinical purposes, it would be envisioned to treat patients with an adenovirus expressing one or both of the TGF-β receptors to block tumor growth or cause tumor regression.

Example 11 Stepwise Sequential Loss of Type III and Type II TGF-β Receptor Expression in Renal Cell Carcinoma

With genomic profiling in human renal cell carcinoma, the data presented above demonstrated a stepwise sequential loss of type III and type II TGF-β receptor expression in association with renal cell carcinogenesis and progression. These findings were confirmed by both immunohistochemistry and real-time PCR in patient-matched tissue samples. This clinical observation was brought to the laboratory to identify relevant in vitro models. Using these models, it was demonstrated that loss of type III TGF-β receptor expression resulted in incremental desensitization to TGF-β and attenuation of TGF-β signaling. Subsequent loss of type II TGF-β receptor resulted in complete loss of TGF-β sensitivity. With in vitro modulation of TGF-β receptor expression, it was demonstrated that reconstitution of the TGF-β signaling pathway resulted in significant growth inhibition and loss of the aggressive phenotype.

These experiments are unique in that clinically relevant observations, which are derived from the evaluation of gene expression in normal renal cortical tissue, localized renal cell carcinoma and metastatic renal cell carcinoma, were brought to the laboratory for validation and experimental manipulation in relevant in vitro models. Other investigators have examined human renal cell carcinoma cell lines and identified alterations in the expression of TGF-β signaling pathway intermediaries, but those observations have not been validated in the clinical biology of renal cell carcinoma. To the investigators' knowledge, few studies have methodically examined the expression of all three TGF-β receptors in patient samples at the protein and mRNA level in an effort to correlate TGF-β receptor expression to disease-specific states of renal cell carcinoma (i.e. localized versus metastatic tumor). A major strength of the present study is that the investigators recognized distinct disease states in renal cell carcinoma, associated them with specific alterations in the TGF-β signaling pathway, and then validated and manipulated the clinical observations in the laboratory.

Although the mechanisms are not well understood, it is clear that TGF-β regulates a large number of diverse biological functions, including cell proliferation, differentiation, cell adhesion, apoptosis, extracellular matrix production, immune regulation, neuroprotection, and early embryonic development. In epithelial cells, the effect of TGF-β is generally to inhibit proliferation, promote cellular differentiation, and regulate interactions with the extracellular matrix. As a direct consequence, aberrations in TGF-β signaling can have a dramatic impact on cellular processes that are critically associated with neoplastic and malignant transformation. Given the well-documented observation that the end result of TGF-β signaling is largely growth inhibitory, it makes intuitive sense that cancer cell would develop mechanisms to escape TGF-β sensitivity. To date, these mechanisms have not been elucidated in human renal cell carcinoma.

Based on the data presented above, the investigators hypothesize that this escape from the growth-inhibitory effects of TGF-β is mediated through the stepwise sequential loss of type III and type II TGF-β receptor expression. To the investigators' knowledge, no one has linked sequential loss of these two types of receptors to carcinogenesis and metastatic progression in oncology. This is the first time that stepwise loss of a single transduction pathway has been associated with important biologic sequelae in a human cancer.

Results presented in the present invention demonstrate that loss of type III TGF-β receptor expression is an early event in renal cell carcinoma biology and that this loss has important sequelae with regard to renal cell carcinoma carcinogenesis and progression. All clinical samples of localized renal cell carcinoma demonstrated loss of type III TGF-β receptor, but had normal expression of type I and type II TGF-β receptors. Replication of this clinical observation in in vitro models demonstrated significant loss of TGF-β sensitivity, manifest as a significant reduction in the growth inhibitory effects of TGF-β1 and significantly reduced TGF-β-mediated transcription. Interestingly, cell lines derived from localized RCC retained type II TGF-β receptor expression and therefore, still demonstrated sensitivity, albeit reduced, to TGF-β. Only with metastatic progression and loss of type II TGF-β receptor expression does the cell become completely resistant to the effects of TGF-β. The investigators hypothesize that this retained, but attenuated, TGF-β signaling seen in local tumors must convey some as yet unrecognized biologic benefit for local tumors that is no longer required, and therefore discarded, with metastatic progression. In fact, this loss of type II TGF-β receptor expression may be an absolute integral component in the cascade of intracellular events that lead to the development of metastatic potential. In keeping with this hypothesis, it has been shown that loss of type I TGF-b receptor expression was one of 40 integral alterations of gene expression to predict for poor prognosis of patients diagnosed with renal cell carcinoma.

In summary, the above results demonstrate a clear link between loss of type III TGF-β receptor expression to a human disease state. Reduced type III TGF-β receptor (TBR3) expression has been reported in human breast tumor cell lines, suggesting that loss of TBR3 expression may be a more ubiquitous phenomena in carcinogenesis, rather than an isolated finding in human RCC biology. The fact that the investigators found down-regulation of TBR3 in every renal cell carcinoma specimen studied to date (35 patients) and that re-expression of TBR3 (in the presence of re-expressed TBR2) completely abolish growth on soft agar suggests an important role for TBR3 in normal renal epithelial homeostasis that must be abrogated for renal cell carcinogenesis and progression to occur. Little attention has been given to TBR3 in normal cell biology or the changes in expression that occur with carcinogenesis and progression. Observations from the present invention would suggest that TBR3 plays an important functional role in signaling and that loss of expression is an important event in the acquisition of the tumorigenic and metastatic phenotype

Example 12 Genomic Profiling for Stage I Papillary Renal Cell Carcinoma and Benign Oncocytoma

FIG. 19 shows hierarchical clustering of genes over-expressed or down-regulated (with at least 2 fold differences) in stage I papillary renal cell carcinoma verses normal renal cortex. Genes over-expressed and down-regulated in stage I papillary renal cell carcinoma are listed in Table 8 and Table 9 respectively. FIG. 20 shows hierarchical clustering of genes over-expressed or down-regulated (with at least 2 fold differences) in benign oncocytoma verses normal renal cortex. Genes over-expressed and down-regulated in benign oncocytoma are listed in Table 10 and Table 11 respectively. FIG. 21 shows venn analysis of gene distribution among stage I renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma. Genes with at least 2-fold differences in expression were filtered at 95% confidence level (CL) in the following 3 t-tests: stage I RCC vs. normal; oncocytoma vs. normal; and stage I papillary renal cell carcinoma vs. normal. Six hundred twenty five genes were present only in stage I RCC (95% CL), 136 genes were present only in oncocytoma (95% CL), 344 genes were present only in stage I papillary renal cell carcinoma (95% CL), and 60 genes were common to stage I RCC, oncocytoma and stage I papillary renal cell carcinoma. FIG. 22 shows venn analysis of gene distribution among stage II renal cell carcinoma (RCC), oncocytoma and stage I papillary renal cell carcinoma. Genes with at least 2-fold differences in expression were filtered at 95% confidence level (CL) in the following 3 t-tests: stage II RCC vs. normal; oncocytoma vs. normal; and stage I papillary renal cell carcinoma vs. normal. One thousand and five genes were present only in stage II RCC (95% CL), 152 genes were present only in oncocytoma (95% CL), 334 genes were present only in stage I papillary renal cell carcinoma (95% CL), and 43 genes were common to stage II RCC, oncocytoma and stage I papillary renal cell carcinoma.

TABLE 8 Genes With Up-Regulated Expression In stage I Papillary Renal Cell Carcinoma Genbank ID Gene Symbol NM_003505 FZD1 AL035683 B4GALT5 R56118 N/A NM_014575 SCHIP1 AI694320 ZNF533 BC031322 N/A BF346665 N/A BC004283 LOC283639 AF302786 GNPTAG AU121975 PAICS NM_016315 GULP1 AL541302 SERPINE2 BG391217 C9orf80 NM_000700 ANXA1 N30188 N/A NM_003651 CSDA AI830227 FLII U20350 CX3CR1 NM_005692 ABCF2 U34074 AKAP1 AB056106 TARSH AU151483 CDH6 BC026260 TTC3 AL133001 SULF2 NM_003358 UGCG NM_001282 AP2B1 AF322067 RAB34 NM_001540 HSPB1 N58363 STATIP1 AF072872 FZD1 BF247552 SLC38A1 X69397 CD24 BC000251 GSK3B BF691447 B4GALT5 AB046817 SYTL2 AF255647 DKFZP566N034 BF344237 N/A AW242720 LOC143381 AA115485 MGC3222 NM_006588 SULT1C2 NM_000546 TP53 N92494 JWA W74580 MGC3222 AF131749 PSK-1 AW026491 CCND2 NM_012410 PSK-1 NM_002800 PSMB9 BF512748 JAK3 AA404269 PRICKLE1 M33376 AKR1C1 AF035321 DNM1 NM_002862 PYGB AF132000 DKFZP564K1964 L07950 HLA-C AF114011 TNFSF13 BF674052 VMP1 AI922599 VIM AF044773 BANF1 NM_015925 LISCH7 NM_001684 ATP2B4 AI123348 CHST11 NM_001304 CPD NM_006762 LAPTM5 NM_000211 ITGB2 AA995910 ALOX5 NM_018965 TREM2 AL353715 STMN3 BC019612 C20orf75 AF086074 N/A NM_005045 RELN AI935123 C14orf78 AL550875 C7orf28B L27624 TFPI2 AL574096 TFPI2 AA005141 MET D86983 D2S448 AW439242 C6orf68 AB000221 CCL18 NM_002121 HLA-DPB1 U17496 PSMB8 U05598 AKR1C1 BF342851 D2S448 BF311866 PTGFRN NM_001449 FHL1 AA954994 N/A Y13710 CCL18 BG170541 MET AB037813 DKFZp762K222 D28124 NBL1 NM_021103 TMSB10 AI949772 N/A AC004382 DKFZP434K046 NM_000248 MITF NM_022154 SLC39A8 AI436813 N/A AF007162 CRYAB NM_015392 NPDC1 AL136585 DKFZp761A132 AB040120 SLC39A8 NM_138473 SP1 AU144387 182-FIP NM_022763 FAD104 AI093231 APBB1IP NM_000235 LIPA AI817079 EXOC7 NM_004385 CSPG2 NM_024801 TARSH BF218922 CSPG2 BF590263 CSPG2 NM_001233 CAV2 AB020690 PNMA2 AW188198 TNFAIP6 NM_007115 TNFAIP6 AI742838 DOCK11 AW117264 N/A AF016266 TNFRSF10B NM_013952 PAX8 AA771779 ZFP90 W72333 FLJ21657 H23979 MOX2 BG542521 PPM2C AF063591 MOX2 BF247383 BMPR2 NM_005114 HS3ST1 BE466145 N/A BC005352 TNFAIP8 AC002045 LOC339047 BC040558 D2LIC U13699 CASP1 NM_002718 PPP2R3A BF476502 MPPE1 BC034275 LOC253982 AF279145 ANTXR1 AV724216 NDRG4 BG165613 N/A NM_018205 LRRC20 NM_022083 C1orf24 NM_006169 NNMT AF141347 TUBA3 NM_000064 C3 AV710838 BCDO2 AI417917 EHD2 AI681260 LILRB1 NM_000389 CDKN1A AF288391 C1orf24 NM_002627 PFKP NM_001975 ENO2 NM_030786 SYNCOILIN NM_006169 NNMT AI417917 EHD2 NM_006868 RAB31 L03203 PMP22 AF199015 VIL2 AI873273 SLC16A6 NM_017821 RHBDL2 BF740152 MYO1F AA954994 N/A AI458735 MGC26717 NM_003254 TIMP1 AI688631 N/A AK026037 N/A BG327863 CD24 NM_016008 D2LIC AI394438 LOC253981 AA947051 D2LIC AI819043 N/A AI378044 UGCG NM_024576 OGFRL1 M76477 GM2A NM_002214 ITGB8 AI879381 ADCK2 NM_000152 GAA H15129 MEIS4 L42024 HLA-C NM_002178 IGFBP6 AI761561 HK2 AA722799 DCBLD2 NM_003255 TIMP2 NM_000107 DDB2 AV699565 CTSC NM_000861 HRH1

TABLE 9 Genes With Down-Regulated Expression In stage I Papillary Renal Cell Carcinoma Genbank ID Gene Symbol AF232217 N/A AI823572 MGC45438 AU154994 SLC13A3 AW979271 N/A AF064103 CDC14A AI524125 PCDH9 AI733474 GPR155 AI767756 HS6ST2 NM_000412 HRG NM_021614 KCNN2 M13149 HRG H17038 N/A NM_002010 FGF9 AI635774 EMCN AW007532 IGFBP5 NM_004070 CLCNKA NM_014621 HOXD4 AI733593 N/A NM_020632 ATP6V0A4 AI697028 FLJ90165 AA897516 PTGER4 NM_024307 MGC4171 J02639 SERPINA5 NM_000085 CLCNKB AA058832 MGC33926 BF059276 N/A BC043647 LOC284578 AL161958 THY1 AL121845 KIAA1847 AY079172 ATP6V0D2 AA928708 CYP8B1 H71135 ADH6 NM_000102 CYP17A1 Z92546 SUSD2 AL558479 THY1 BC005314 ALDOB NM_173591 FLJ90579 BF510426 N/A AF331844 SOST X77737 SLC4A1 NM_004392 DACH1 BC001077 LOC87769 AA218868 THY1 BF478120 RECQL5 BC041158 CYP4A11 AI623321 MTP AI796189 PAH NM_021161 KCNK10 NM_000163 GHR AL136880 ESPN NM_024426 WT1 M61900 PTGDS AW963951 SIAT7C AW340588 MAN1C1 AI263078 SLC23A3 BF130943 PPAPDC1 AI732596 N/A AA603467 ZNF503 R41565 N/A AI951185 NR2F1 NM_002609 PDGFRB NM_006984 CLDN10 BG413612 N/A D64137 CDKN1C AK026344 PEPP2 AI670852 PTPRB AI693153 GABRB3 NM_001393 ECM2 N93191 PR1 BC005090 AGMAT NM_000717 CA4 D38300 PTGER3 AI650260 N/A BC024226 IFRG15 BC006294 DHRS10 NM_003039 SLC2A5 AI675836 SORCS1 NM_005276 GPD1 NM_014298 QPRT M10943 MT2A NM_005952 MT1X NM_002450 MT1X NM_002910 RENBP BF246115 MT1F AF078844 MT1F AF170911 SLC23A1 AF333388 MT1H NM_003500 ACOX2 AA995925 N/A NM_001218 CA12 BF432333 FLJ31196 NM_001385 DPYS NM_003052 SLC34A1 NM_000778 CYP4A11 AL136551 SESN2 NM_000792 DIO1 NM_016725 FOLR1 NM_019101 APOM NM_014270 SLC7A9 AF124373 SLC22A6 NM_016327 UPB1 NM_024734 CLMN NM_016527 HAO2 NM_003645 SLC27A2 AB051536 FLJ14957 NM_025149 FLJ20920 BC005939 PTGDS AL574184 HPGD NM_000161 GCH1 H57166 N/A NM_000597 IGFBP2 NM_000790 DDC NM_004668 MGAM NM_021027 UGT1A6 AF348078 GPR91 NM_016347 NAT8 AF338650 PDZK3 BE221817 CNTN3 NM_004476 FOLH1 NM_004615 TM4SF2 NM_023940 RASL11B AI742872 SLC2A12 BC001196 HS6ST1 AW195353 TFCP2L1 NM_003122 SPINK1 NM_144707 PROM2 AI653981 L1CAM AI796169 GATA3 M96789 GJA4 N74607 AQP3 NM_014059 RGC32 AI572079 SNAI2 AI056877 N/A NM_006206 PDGFRA AW771314 MGC35434 NM_016955 SLA/LP AI569804 LOC375295 NM_001584 C11orf8 BG261252 EVI1 NM_006226 PLCL1 NM_001172 ARG2 AL050264 TU3A BC003070 GATA3 AL120332 MGC20785 NM_000459 TEK AW242836 LOC120224 AI926697 Gup1 NM_000486 AQP2 AI870306 IRX1 AW264204 CLDN11 BF431989 THRB AI459140 N/A NM_001864 COX7A1 AI471866 SLC7A13 AI653107 NRK NM_004466 GPC5 BF195936 KRT18L1 NM_022454 SOX17 AW299531 HOXD10 AL137716 AQP6 AI332407 SFRP1 AL565812 PTN AI452457 LOC199920 AI281593 DCN M21692 ADH1B AI660243 TMPRSS2 AI754423 FLJ38507 AA759244 FXYD4 U75667 ARG2 NM_000930 PLAT AF083105 SOX13 NM_013231 FLRT2 BI825302 PR1 NM_003012 SFRP1 AF138300 DCN AU155612 N/A BG435302 EBF NM_005978 S100A2 NM_000900 MGP AK026748 DKFZP761M1511 J03208 DBT NM_002345 LUM NM_006623 PHGDH AF063606 my048 NM_001647 APOD AI935541 N/A NM_005558 LAD1 AW138125 PRODH2 NM_003877 SOCS2 AI768894 CGN AW772192 N/A AF094518 ESRRG T40942 ANGPTL3 NM_001146 ANGPT1 AI242023 N/A BF970431 N/A NM_005670 EPM2A AW071744 KCNJ10 AI928242 TFCP2L1 AI769774 LOC155006 AW274034 USP2 NM_004633 IL1R2 NM_003289 TPM2 BF512388 C10orf58 BC005830 ANXA9 NM_000362 TIMP3 NM_001438 ESRRG AU146204 ENPP6 AA775681 FLJ23091 AI393205 ACY-3 AF017987 SFRP1 NM_005951 MT1H NM_005950 MT1G NM_021805 SIGIRR AA557324 CYP4X1 BF528646 DKFZP564I1171 AW340112 LOC401022 R73554 IGFBP5 AI826437 N/A AV720650 KIAA0888 AA780067 HS3ST3B1 NM_000640 IL13RA2 AI806338 TBX3 NM_003155 STC1 AA931562 N/A AI694325 N/A AF205940 EMCN NM_001290 LDB2 NM_016242 EMCN AW014927 CALB1 AI758950 SLC26A7 AK024256 KIAA1573 BF726212 ANK2 AI985987 SCNN1G AW242408 UPP2 NM_000860 HPGD BF447963 KIAA0962 BF941499 GPR116 AW242409 N/A BF509031 ATP6V1G3 NM_000934 SERPINF2 BF248364 AF15Q14 AL534095 FLJ23091 NM_004929 CALB1 AI222435 N/A NM_005397 PODXL AI090268 N/A AI300520 STC1 BC006236 MGC11324 NM_024609 NES NM_002591 PCK1 NM_005410 SEPP1 AB020630 PPP1R16B AF022375 VEGF NM_016246 DHRS10 AA873542 SLC6A19 U95090 PRODH2 D26054 FBP1 AI732994 MGC13034 NM_000151 G6PC AK025651 PNAS-4 AF161441 N/A AF161454 APOM NM_022129 MAWBP AI733515 MGC52019 NM_001443 FABP1 AI433463 MME AL049313 N/A BF195998 ALDOB NM_022829 SLC13A3 NM_000035 ALDOB NM_007287 MME NM_003399 XPNPEP2 NM_000196 HSD11B2 BF431313 N/A NM_004844 SH3BP5 NM_003206 TCF21 AI311917 DPYS AA843963 PRLR NM_017753 PRG-3 NM_006633 IQGAP2 NM_001133 AFM T90064 N/A BF696216 N/A NM_004413 DPEP1 Z98443 FLJ38736 NM_018456 EAF2 AW771563 N/A NM_014495 ANGPTL3 AI074145 KMO NM_000896 CYP4F3 NM_001072 UGT1A6 AI631993 N/A NM_000277 PAH M74220 PLG AI935789 UMOD NM_002472 MYH8 BC020873 CLCNKA NM_000550 TYRP1 AA806965 BTNL9 NM_020163 LOC56920 NM_004490 GRB14 AA788946 COL12A1 AW242315 N/A AI735586 LOC152573 R88990 N/A NM_003278 TNA NM_007180 TREH AW173045 TBX2 U28049 TBX2 NM_001395 DUSP9 NM_000336 SCNN1B U43604 N/A BC029135 N/A NM_005414 SKIL BQ894022 PDE1A NM_013335 GMPPA NM_003221 TFAP2B BF057634 HOXD8 AA523172 N/A AF319520 ARG99 NM_002885 RAP1GA1 NM_003361 UMOD NM_000142 FGFR3 NM_000893 KNG1 BC029135 N/A NM_147174 HS6ST2 NM_000218 KCNQ1 U03884 KCNJ1 X83858 PTGER3 BF439270 N/A AA911235 MST1 NM_000955 PTGER1 NM_022844 MYH11 BC042069 N/A NM_005518 HMGCS2 NM_001963 EGF AI632015 SLC12A1 AF339805 N/A BF106962 FAM3B NM_005019 PDE1A AU146305 PDE1A NM_000663 ABAT AU119437 LOC144997 BC036095 DRP2 R49295 N/A AI623202 PRDM16 AW452355 N/A AA563621 HSPB6 X15217 SKIL AK095719 N/A AI056187 N/A AI668598 N/A AI700882 SLC13A3 NM_000963 PTGS2 AW051712 N/A AL832099 MGC33190 AK057337 LOC145820 AW300204 SLC30A8 NM_005856 RAMP3 AI458003 CYYR1 AK026877 N/A AI632567 N/A U91903 FRZB AF352728 FLJ12541 BM128432 IGFBP5 NM_003102 SOD3 BE676272 TACC1 AI692180 PPFIBP2 AL544576 LOC92162 NM_017688 BSPRY AU146310 N/A AI912976 RASGRF2 U83508 ANGPT1 L47125 GPC3 NM_000663 ABAT

TABLE 10 Genes With Up-Regulated Expression In Benign Oncocytoma Genbank ID Gene Symbol NM_005114 HS3ST1 AA650558 GNAS BF062244 LIN7A NM_030674 SLC38A1 NM_014766 SCRN1 BC002471 CPLX1 AF183421 RAB31 AK022100 KIAA0256 BF508244 AKR1C2 BG772511 N/A AB037848 SYT13 AK055769 N/A T58048 N/A NM_012105 BACE2 AA992805 LEF1 AK026420 DMN NM_024812 BAALC AI057226 N/A AW138767 ELOVL7 NM_013233 STK39 AF178532 BACE2 AI521166 LOC283104 AA005023 NOD27 AV725364 GPRC5B AW195581 GPSM2 BG503479 B4GALT6 BF031829 DSG2 AW975728 SLC16A7 NM_022495 C14orf135 AA703159 N/A BF247552 SLC38A1 NM_001673 ASNS NM_024622 FLJ21901 AI565054 N/A AW058459 LOC134285 NM_001233 CAV2 BC036550 N/A BE464483 N/A NM_002512 NME2 AF178532 BACE2

TABLE 11 Genes With Down-Regulated Expression In Benign Oncocytoma Genbank ID Gene Symbol BF593625 SYK AI310001 FLJ22789 NM_006206 PDGFRA NM_003740 KCNK5 AW138125 PRODH2 NM_000336 SCNN1B BC005314 ALDOB AI796189 PAH NM_013363 PCOLCE2 NM_004466 GPC5 AI627531 N/A U28055 MSTP9 NM_152759 MGC35140 AW052159 N/A NM_017712 PGPEP1 AI961231 TOX AI767962 BNC2 AF350881 TRPM6 AU146418 N/A BE875072 N/A AI653981 L1CAM AI634662 SLC13A3 NM_000486 AQP2 AW206292 AQP2 AI572079 SNAI2 AI694118 N/A NM_000142 FGFR3 U78168 RAPGEF3 AI913600 UNQ846 W93847 MUC15 NM_004616 TM4SF3 AI935789 UMOD NM_007180 TREH AL110152 CD109 AW051599 N/A AI796169 GATA3 AF017987 SFRP1 BE550027 DKFZp761N1114 AA535065 KIAA1847 NM_003361 UMOD AI263078 SLC23A3 M13149 HRG AF278532 NTN4 AI632015 SLC12A1 NM_000412 HRG NM_000893 KNG1 BG398937 KNG AL049977 CLDN8 N74607 AQP3 AW071744 KCNJ10 AW015506 AQP2 AI927000 SOSTDC1 AI471866 SLC7A13 NM_001099 ACPP NM_005074 SLC17A1 AA995925 N/A AF352728 FLJ12541 BF343007 TFAP2A NM_016929 CLIC5 AA911235 MST1 AA639753 N/A NM_004887 CXCL14 AW771565 AIM1 AI264671 N/A BF510426 N/A AV728958 TLN2 T90064 N/A AA218868 THY1 NM_003104 SORD AJ292204 AGXT2 AI056359 MAPT AL568422 DZIP1 AF339805 N/A NM_000163 GHR AI042017 NPL AW340457 N/A BF431199 DEHAL1 BF432254 MGC15937 AI368018 GPD1 AF144103 CXCL14 NM_016725 FOLR1 NM_000050 ASS AA693817 N/A NM_004929 CALB1 NM_000592 C4A AL574184 HPGD AA676742 DMGDH AI631993 N/A AI566130 AK3 AW024233 GLYAT AA873542 SLC6A19 AK026966 AK3 NM_022829 SLC13A3 NM_005950 MT1G AV700405 MGC52019 AI733515 MGC52019 NM_000860 HPGD U95090 PRODH2 NM_001385 DPYS BG401568 SLC16A9 NM_000846 GSTA1 BF195998 ALDOB NM_004413 DPEP1 NM_000151 G6PC NM_006744 RBP4 NM_013410 AK3 NM_000035 ALDOB AK026411 ALDOB AL135960 CYP4A11 M74220 PLG NM_001713 BHMT AW614558 SLC39A5 Z92546 SUSD2 NM_000778 CYP4A11 NM_000792 DIO1 AI222435 N/A D26054 FBP1 AW025165 SLC22A8 NM_007287 MME AW274034 USP2 NM_147174 HS6ST2 AA074145 PRODH AL049176 CHRDL1 NM_020353 PLSCR4 NM_024803 TUBAL3 D16931 ALB NM_019076 UGT1A10 AF138303 DCN D13705 CYP4A11 NM_000587 C7 R49295 N/A NM_000385 AQP1 AI669229 RARRES1 U36189 C5orf13 AL110135 FLJ14753 AW271605 N/A BF358386 N/A NM_016270 KLF2 AA905508 LOC128153 NM_021630 PDLIM2 AA915989 TBC1D13 AL565812 PTN AI990790 N/A BC041158 CYP4A11 NM_138474 N/A NM_002899 RBP1 AK024256 KIAA1573 AW779672 SLC17A1 NM_021161 KCNK10 BF196891 TPMT AY028896 CARD10 NM_018456 EAF2 NM_017806 FLJ20406 X59065 FGF1 AI650353 DACH1 AW771563 N/A BF431313 N/A NM_000896 CYP4F3 BC005090 AGMAT U24267 ALDH4A1 AI090268 N/A AW014927 CALB1 AL023553 PIPPIN AL049313 N/A AK021539 NCAG1 AI220117 MGST1 NM_020300 MGST1 NM_022568 ALDH8A1 BE874872 FAM20C NM_004668 MGAM BF033242 CES2 BC004542 PLXNB2 NM_000204 F NM_004525 LRP2 AA442149 MAF NM_000049 ASPA AI830469 TFEC NM_003759 SLC4A4 AF169017 FTCD AF170911 SLC23A1 AA865601 LOC123876 AA863031 MGC32871 AW136060 SLC13A2 NM_003041 SLC5A2 NM_021924 MUCDHL AW299568 N/A AI927941 N/A AI433463 MME AL365347 SLC7A8 AA502331 PRAP1 NM_024709 FLJ14146 AF289024 FTCD NM_017614 BHMT2 NM_016347 NAT8 NM_000277 PAH NM_000316 PTHR1 NM_001091 ABP1 NM_000790 DDC BF217861 MT1E BF447963 KIAA0962 NM_001081 CUBN NM_018484 SLC22A11 AW192692 N/A BF000045 TINAG BC005830 ANXA9 NM_025257 C6orf29 NM_020973 GBA3 NM_001977 ENPEP AI632692 N/A BI825302 PR1 L12468 ENPEP AL571375 SCD4 AL136858 ZMYND12 NM_024027 COLEC11 NM_014934 DZIP1 BG496631 FBI4 NM_018265 FLJ10901 AI770035 UPB1 AF177272 UGT2B28 NM_004392 DACH1 N95363 CDKN1C AF261715 FOLH1 NM_000042 APOH NM_001393 ECM2 R88990 N/A AA557324 CYP4X1 AF116645 ALB BC015993 MGC27169 AL558479 THY1 NM_000785 CYP27B1 AW051926 AMN AA928708 CYP8B1 BE407830 KIFC3 AI431643 RRAS2 AF001434 EHD1 BC005894 FMO2 NM_006798 UGT2A1 BF217861 MT1E

The following references were cited herein:

-   Copland et al., Recent Prog. Horm. Res. 58:25-53 (2003). -   Copland et al., Oncogene 22:8053-62 (2003). -   Grossman et al., J. Surg. Oncol. 28:237-244 (1985). -   Trifillis, Exp. Nephrol. 7:353-359 (1999). 

1.-21. (canceled)
 22. A method of detecting a renal cell cancer comprising the steps of: obtaining one or more biological samples comprising renal tissue or renal cells from an individual; determining a gene expression level of GATA3 in the sample; and performing statistical analysis on the expression level of the GATA3 gene as compared to that expressed in normal biological samples comprising renal tissue or renal cells, wherein statistically down-regulated gene expression levels would indicate said individual has papillary or clear cell renal cell cancer.
 23. The method of claim 22, further comprising the step of measuring the expression levels of TFCP2L1, wherein down-regulated gene expression levels of TFCP2L1 indicate the individual has papillary or clear cell renal cell cancer.
 24. The method of claim 22, further comprising the step of measuring the expression levels of TFAP2B, wherein down-regulated gene expression levels of TFAP2B indicate the individual has papillary or clear cell renal cell cancer.
 25. The method of claim 22, further comprising the step of measuring the expression levels of DMRT2, wherein down-regulated gene expression levels of DMRT2 indicate the individual has papillary or clear cell renal cell cancer.
 26. The method of claim 22, further comprising the step of measuring the expression levels of TFCP2L1, TFAP2B, and DMRT2, wherein down-regulated gene expression levels of TFCP2L1, TFAP2B, and DMRT2 indicate the individual has papillary or clear cell renal cell cancer.
 27. The method of claim 22, wherein the step of determining the gene expression level of the GATA3 gene is by DNA microarray, hierarchical cluster analysis, real-time PCR, RT-PCR, or northern analysis.
 28. The method of claim 22, wherein the renal cell cancer is a Stage I, II, II or IV renal cancer.
 29. A method of detecting a renal cell cancer comprising the steps of: obtaining one or more biological samples comprising renal tissue or renal cells from an individual; determining a gene expression level of GATA3 in the sample and at least one gene selected from TFCP2L1, TFAP2B, and DMRT2; and performing statistical analysis on the expression level of the GATA3 gene as compared to that expressed in normal biological samples comprising renal tissue or renal cells, wherein statistically down-regulated gene expression levels would indicate said individual has papillary or clear cell renal cell cancer.
 30. The method of claim 29, further comprising the step of measuring the expression levels of TFCP2L1, TFAP2B, and DMRT2, wherein down-regulated gene expression levels of TFCP2L1, TFAP2B, and DMRT2 indicate the individual has papillary or clear cell renal cell cancer.
 31. The method of claim 29, wherein the step of determining the gene expression level of the GATA3 gene is by DNA microarray, hierarchical cluster analysis, real-time PCR, RT-PCR, or northern analysis.
 32. The method of claim 29, wherein the renal cell cancer is a Stage I, II, II or IV renal cancer. 